Rational Design of Molecularly Imprinted Polymers for Curcuminoids Binding: Computational and Experimental Approaches for the Selection of Functional Monomers.

Abstract

Molecularly imprinted polymers (MIPs) have emerged as bespoke materials with versatile molecular applications. In this study, we propose a proof of concept for a methodology employing molecular dynamics (MD) simulations to guide the selection of functional monomers for curcuminoid binding in MIPs. Curcumin, demethoxycurcumin, and bisdemethoxycurcumin are phenolic compounds widely employed as spices, pigments, additives, and therapeutic agents, representing the three main curcuminoids of interest. Through MD simulations, we investigated prepolymerization mixtures composed of various functional monomers, including acrylamide (ACA), acrylic acid (AA), methacrylic acid (MAA), and N-vinylpyrrolidone (NVP), with ethylene glycol dimethacrylate (EGDMA) as the cross-linker and acetonitrile as the solvent. Curcumin was selected as the template molecule due to its structural similarity to the other curcuminoids. Notably, the prepolymerization mixture containing NVP as the functional monomer demonstrated superior molecular recognition capabilities toward curcumin. This observation was supported by higher functional monomer molecules surrounding the template, a lower total nonbonded energy between the template and monomer, and a greater number of hydrogen bonds in the aggregate. These findings suggest a stronger affinity between the functional monomer NVP and the template. We synthesized, characterized, and conducted binding tests on the MIPs to validate the MD simulation results. The experimental binding tests confirmed that the MIP-NVP exhibited higher binding capacity. Consequently, based on MD simulations, our computational methodology effectively guided the selection of the functional monomer, leading to MIPs with binding capacity for curcuminoids. The outcomes of this study provide a valuable reference for the rational design of MIPs through MD simulations, facilitating the selection of components for MIPs. This computational approach holds the potential for extension to other templates, establishing a robust methodology for the rational design of MIPs.